GPU × use-case guide · Embeddings
Is the RTX A6000 a good GPU for embeddings?
The RTX A6000 is a ampere NVIDIA GPU with 48 GB GDDR6 (768 GB/s), 38.7 TFLOPS BF16 / 38.7 TFLOPS FP8, and a 300 W TDP. Embeddings workloads care most about maximum batch throughput on small encoder models — pure tokens-per-dollar. Here's how the RTX A6000 measures up.
What models fit on a single RTX A6000?
Weights only, reserving ~25% of the 48 GB for KV cache, activations and fragmentation. ✓ = fits on one card.
| Model | BF16 | FP8 | INT4 |
|---|---|---|---|
| Llama 3.1 8B | ✓ | ✓ | ✓ |
| Qwen 2.5 14B | ✓ | ✓ | ✓ |
| Gemma 2 27B | — | ✓ | ✓ |
| Mixtral 8x7B (MoE) | — | — | ✓ |
| Llama 3.3 70B | — | — | ✓ |
| Qwen 2.5 72B | — | — | ✓ |
| Llama 3.1 405B | — | — | — |
Largest single-card fit: Qwen 2.5 14B at BF16, Gemma 2 27B at FP8, Qwen 2.5 72B at INT4. Bigger models need tensor-parallel across 8 cards.
RTX A6000 for embeddings, specifically
Embeddings is throughput-bound rather than VRAM-bound, so the RTX A6000's 768 GB/s of bandwidth and 38.7 TFLOPS matter more than raw capacity. Because it runs offline, batch aggressively to push tokens-per-dollar down. Size it precisely on the calculator.
RTX A6000 pricing across providers
| Provider | On-demand $/hr | Reserved $/hr |
|---|---|---|
| tensordock | $0.69 | — |
| vast_ai | $0.79 | — |
| lambda | $0.99 | — |
| runpod | $1.09 | — |
Verdict
At 48 GB, the RTX A6000 is a solid mid-to-high-tier choice for embeddings: single-card up to Qwen 2.5 14B (BF16) or Gemma 2 27B (FP8), and cost-effective at ~$0.69/hr.
See full RTX A6000specs & pricing, size your model on the calculator, or compare every GPU on the GPU list.